




'''simple docstring'''


from typing import List, Optional, TypeVar

from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interleave_iterable_datasets
from .splits import NamedSplit
from .utils import logging
from .utils.py_utils import Literal


_snake_case : Union[str, Any]  				=						logging.get_logger(__name__)


_snake_case : List[str]  				=						TypeVar('DatasetType', Dataset, IterableDataset)
def 						snake_case_       (UpperCamelCase			:    List[DatasetType]					,		UpperCamelCase			:    Optional[List[float]] = None					,		UpperCamelCase			:    Optional[int] = None					,		UpperCamelCase			:    Optional[DatasetInfo] = None					,		UpperCamelCase			:    Optional[NamedSplit] = None					,		UpperCamelCase			:    Literal["first_exhausted", "all_exhausted"] = "first_exhausted"					,		):





							'''simple docstring'''


							from .arrow_dataset import Dataset
							from .iterable_dataset import IterableDataset

							if not datasets:
														raise ValueError('''Unable to interleave an empty list of datasets.''' )
							for i, dataset in enumerate(UpperCamelCase ):
														if not isinstance(UpperCamelCase					,		(Dataset, IterableDataset) ):
																					if isinstance(UpperCamelCase					,		(DatasetDict, IterableDatasetDict) ):
																												if not dataset:
																																			raise ValueError(
																																			    f'Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} '
																																			    '''is an empty dataset dictionary.''' )
																												raise ValueError(
																												    f'Dataset at position {i} has at least one split: {list(UpperCamelCase )}\n'
																												    f'Please pick one to interleave with the other datasets, for example: dataset[\'{next(iter(UpperCamelCase ) )}\']' )
																					raise ValueError(
																					    f'Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(UpperCamelCase ).__name__}.' )
														if i == 0:
																					_a	,				_a      	=							(
																					    (Dataset, IterableDataset) if isinstance(UpperCamelCase					,		UpperCamelCase ) else (IterableDataset, Dataset)
																					)
														elif not isinstance(UpperCamelCase					,		UpperCamelCase ):
																					raise ValueError(
																					    f'Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects.' )
							if stopping_strategy not in ["first_exhausted", "all_exhausted"]:
														raise ValueError(f'{stopping_strategy} is not supported. Please enter a valid stopping_strategy.' )
							if dataset_type is Dataset:
														return _interleave_map_style_datasets(
														    UpperCamelCase					,		UpperCamelCase					,		UpperCamelCase					,		info=UpperCamelCase					,		split=UpperCamelCase					,		stopping_strategy=UpperCamelCase )
							else:
														return _interleave_iterable_datasets(
														    UpperCamelCase					,		UpperCamelCase					,		UpperCamelCase					,		info=UpperCamelCase					,		split=UpperCamelCase					,		stopping_strategy=UpperCamelCase )

def 						snake_case_       (UpperCamelCase			:    List[DatasetType]					,		UpperCamelCase			:    Optional[DatasetInfo] = None					,		UpperCamelCase			:    Optional[NamedSplit] = None					,		UpperCamelCase			:    int = 0					,		):





							'''simple docstring'''


							if not dsets:
														raise ValueError('''Unable to concatenate an empty list of datasets.''' )
							for i, dataset in enumerate(UpperCamelCase ):
														if not isinstance(UpperCamelCase					,		(Dataset, IterableDataset) ):
																					if isinstance(UpperCamelCase					,		(DatasetDict, IterableDatasetDict) ):
																												if not dataset:
																																			raise ValueError(
																																			    f'Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} '
																																			    '''is an empty dataset dictionary.''' )
																												raise ValueError(
																												    f'Dataset at position {i} has at least one split: {list(UpperCamelCase )}\n'
																												    f'Please pick one to interleave with the other datasets, for example: dataset[\'{next(iter(UpperCamelCase ) )}\']' )
																					raise ValueError(
																					    f'Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(UpperCamelCase ).__name__}.' )
														if i == 0:
																					_a	,				_a      	=							(
																					    (Dataset, IterableDataset) if isinstance(UpperCamelCase					,		UpperCamelCase ) else (IterableDataset, Dataset)
																					)
														elif not isinstance(UpperCamelCase					,		UpperCamelCase ):
																					raise ValueError(
																					    f'Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects.' )
							if dataset_type is Dataset:
														return _concatenate_map_style_datasets(UpperCamelCase					,		info=UpperCamelCase					,		split=UpperCamelCase					,		axis=UpperCamelCase )
							else:
														return _concatenate_iterable_datasets(UpperCamelCase					,		info=UpperCamelCase					,		split=UpperCamelCase					,		axis=UpperCamelCase )


from __future__ import annotations

import math

import numpy as np
from numpy.linalg import norm


def 	lowerCamelCase					(	UpperCamelCase     :				np.ndarray			,       UpperCamelCase     :				np.ndarray							)   ->    float:
		return math.sqrt(sum(pow(a - b			,       2							) for a, b in zip(UpperCamelCase			,       UpperCamelCase							)							)							)


def 	lowerCamelCase					(	UpperCamelCase     :				np.ndarray			,       UpperCamelCase     :				np.ndarray							)   ->    list[list[list[float] | float]]:

		if dataset.ndim != value_array.ndim:
				_lowerCamelCase				   =  (
				    'Wrong input data\'s dimensions... '
				    F"""dataset : {dataset.ndim}, value_array : {value_array.ndim}"""
				)
				raise ValueError(UpperCamelCase							)

		try:
				if dataset.shape[1] != value_array.shape[1]:
						_lowerCamelCase				   =  (
						    'Wrong input data\'s shape... '
						    F"""dataset : {dataset.shape[1]}, value_array : {value_array.shape[1]}"""
						)
						raise ValueError(UpperCamelCase							)
		except IndexError:
				if dataset.ndim != value_array.ndim:
						raise TypeError('Wrong shape'							)

		if dataset.dtype != value_array.dtype:
				_lowerCamelCase				   =  (
				    'Input data have different datatype... '
				    F"""dataset : {dataset.dtype}, value_array : {value_array.dtype}"""
				)
				raise TypeError(UpperCamelCase							)

		_lowerCamelCase				   =  []

		for value in value_array:
				_lowerCamelCase				   =  euclidean(UpperCamelCase			,       dataset[0]							)
				_lowerCamelCase				   =  dataset[0].tolist()

				for dataset_value in dataset[1:]:
						_lowerCamelCase				   =  euclidean(UpperCamelCase			,       UpperCamelCase							)

						if dist > temp_dist:
								_lowerCamelCase				   =  temp_dist
								_lowerCamelCase				   =  dataset_value.tolist()

				answer.append([vector, dist]							)

		return answer


def 	lowerCamelCase					(	UpperCamelCase     :				np.ndarray			,       UpperCamelCase     :				np.ndarray							)   ->    float:
		return np.dot(UpperCamelCase			,       UpperCamelCase							) / (norm(UpperCamelCase							) * norm(UpperCamelCase							))


if __name__ == "__main__":
				import doctest

				doctest.testmod()